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36871622f1
This is follow-up of #164912 to mark unused C++ parameters to improve code readability. Pull Request resolved: https://github.com/pytorch/pytorch/pull/165121 Approved by: https://github.com/Skylion007
102 lines
2.5 KiB
C++
102 lines
2.5 KiB
C++
#pragma once
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#include <array>
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#include <cstdint>
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#include <memory>
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#include <stack>
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#include <string>
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#include <unordered_map>
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#include <utility>
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#include <vector>
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#include <torch/csrc/profiler/events.h>
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#include <c10/util/Exception.h>
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namespace torch::profiler::impl::linux_perf {
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/*
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* Maximum number of events supported
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* This stems from the hardware limitation on CPU performance counters, and the
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* fact that we don't support time multiplexing just yet.
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* Time multiplexing involves scaling the counter values proportional to
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* the enabled and running time or running the workload multiple times.
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*/
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constexpr uint8_t MAX_EVENTS = 4;
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struct PerfCounter {
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uint64_t value; /* The value of the event */
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uint64_t time_enabled; /* for TIME_ENABLED */
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uint64_t time_running; /* for TIME_RUNNING */
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};
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/*
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* Basic perf event handler for Android and Linux
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*/
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class PerfEvent {
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public:
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explicit PerfEvent(std::string& name) : name_(name) {}
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PerfEvent(const PerfEvent& other) = delete;
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PerfEvent& operator=(const PerfEvent&) = delete;
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PerfEvent& operator=(PerfEvent&& other) noexcept {
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if (this != &other) {
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fd_ = other.fd_;
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other.fd_ = -1;
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name_ = std::move(other.name_);
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}
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return *this;
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}
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PerfEvent(PerfEvent&& other) noexcept {
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*this = std::move(other);
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}
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~PerfEvent();
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/* Setup perf events with the Linux Kernel, attaches perf to this process
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* using perf_event_open(2) */
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void Init();
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/* Stop incrementing hardware counters for this event */
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void Disable() const;
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/* Start counting hardware event from this point on */
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void Enable() const;
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/* Zero out the counts for this event */
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void Reset() const;
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/* Returns PerfCounter values for this event from kernel, on non supported
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* platforms this always returns zero */
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uint64_t ReadCounter() const;
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private:
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/* Name of the event */
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std::string name_;
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int fd_ = -1;
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};
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class PerfProfiler {
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public:
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/* Configure all the events and track them as individual PerfEvent */
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void Configure(std::vector<std::string>& event_names);
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/* Enable events counting from here */
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void Enable();
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/* Disable counting and fill in the caller supplied container with delta
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* calculated from the start count values since last Enable() */
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void Disable(perf_counters_t& /*vals*/);
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private:
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uint64_t CalcDelta(uint64_t start, uint64_t end) const;
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void StartCounting() const;
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void StopCounting() const;
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std::vector<PerfEvent> events_;
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std::stack<perf_counters_t> start_values_;
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};
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} // namespace torch::profiler::impl::linux_perf
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